Name
Title | ||
|---|---|---|
Dimensionality Reduction for Anomaly Detection in Electrocardiography: A Manifold Approach |
Abstract | ||
|---|---|---|
ECG analysis is universal and important in miscellaneous medical applications. However, high computation complexity is a problem which has been shown in several levels of conventional data mining algorithms for ECG analysis. In this paper, we presented a novel manifold approach to visualize and analyze the ECG signal. According to regularity of the data, our algorithm can discover the intrinsic structure and represent the streaming data with a 1-D manifold on a 2-D space. Furthermore, the proposed algorithm can reliably detect the anomaly in ECG streaming data. We evaluated the performance of the algorithm with two different anomalies in wearable applications: for the anomaly from heart disorders such as apnea, arrythmia, our algorithm could achieve up to 90% recognition rate, for the anomaly from the ECG device, our algorithm could detect the outlier with 100%. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/BSN.2012.12 | BSN |
Keywords | Field | DocType |
different anomaly,ecg device,manifold approach,dimensionality reduction,conventional data mining algorithm,ecg signal,novel manifold approach,heart disorder,ecg analysis,anomaly detection,1-d manifold,2-d space,proposed algorithm,manifold,feature extraction,electrodes,heart,data mining,manifolds,computational complexity | Anomaly detection,Data mining,Dimensionality reduction,Pattern recognition,Heart disorder,Computer science,Wearable computer,Outlier,Feature extraction,Artificial intelligence,Electrocardiography,Manifold | Conference |
Citations | PageRank | References |
9 | 2.32 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhinan Li | 1 | 43 | 7.08 |
| Wenyao Xu | 2 | 615 | 77.06 |
| Anpeng Huang | 3 | 151 | 21.31 |
| Majid Sarrafzadeh | 4 | 3103 | 317.63 |